Triple
T6483995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Altdorf |
E146462
|
entity |
| Predicate | degreeTypeGrantedToLeibniz |
P45182
|
FINISHED |
| Object | doctorate in law |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: doctorate in law | Statement: [University of Altdorf, degreeTypeGrantedToLeibniz, doctorate in law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeTypeGrantedToLeibniz Context triple: [University of Altdorf, degreeTypeGrantedToLeibniz, doctorate in law]
-
A.
degreeGrantedBy
chosen
Indicates that a specific academic degree was officially conferred by a particular granting institution.
-
B.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
C.
honorificDegree
Indicates that an entity has been awarded an honorary academic degree or title, typically in recognition of merit rather than completion of formal study.
-
D.
degreeGrantingStatus
Indicates whether an institution or program has the authority to confer formal academic degrees.
-
E.
hasHonoraryDegreeFrom
Indicates that an individual has been awarded an honorary degree by a particular institution.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a6de31c81909dd99d105f5bb4c2 |
completed | March 22, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:52 p.m.